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化学多元宇宙与食品化学的多样性。

Chemical Multiverse and Diversity of Food Chemicals.

机构信息

DIFACQUIM Research Group, Department of Pharmacy, School of Chemistry, Universidad Nacional Autónoma de México, Avenida Universidad 3000, Mexico City 04510, Mexico.

出版信息

J Chem Inf Model. 2024 Feb 26;64(4):1229-1244. doi: 10.1021/acs.jcim.3c01617. Epub 2024 Feb 14.

DOI:10.1021/acs.jcim.3c01617
PMID:38356237
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10900296/
Abstract

Food chemicals have a fundamental role in our lives, with an extended impact on nutrition, disease prevention, and marked economic implications in the food industry. The number of food chemical compounds in public databases has substantially increased in the past few years, which can be characterized using chemoinformatics approaches. We and other groups explored public food chemical libraries containing up to 26,500 compounds. This study aimed to analyze the chemical contents, diversity, and coverage in the chemical space of food chemicals and additives and, from here on, food components. The approach to food components addressed in this study is a public database with more than 70,000 compounds, including those predicted via techniques. It was concluded that food components have distinctive physicochemical properties and constitutional descriptors despite sharing many chemical structures with natural products. Food components, on average, have large molecular weights and several apolar structures with saturated hydrocarbons. Compared to reference databases, food component structures have low scaffold and fingerprint-based diversity and high structural complexity, as measured by the fraction of sp carbons. These structural features are associated with a large fraction of macronutrients as lipids. Lipids in food components were decompiled by an analysis of the maximum common substructures. The chemical multiverse representation of food chemicals showed a larger coverage of chemical space than natural products and FDA-approved drugs by using different sets of representations.

摘要

食品化学物质在我们的生活中起着基础性的作用,对营养、疾病预防有着深远的影响,并在食品工业中具有显著的经济意义。近年来,公共数据库中食品化学物质的数量大幅增加,可以使用化学生信方法对其进行描述。我们和其他团队探索了包含多达 26500 种化合物的公共食品化学物质库。本研究旨在分析食品化学物质和添加剂(以及从这里开始的食品成分)的化学内容、多样性和在化学空间中的覆盖范围。本研究中所采用的食品成分方法是一个包含超过 70000 种化合物的公共数据库,其中包括通过预测技术预测的化合物。研究得出的结论是,尽管食品成分与天然产物共享许多化学结构,但它们具有独特的物理化学性质和结构描述符。食品成分的平均分子量较大,具有多个非极性结构和饱和烃。与参考数据库相比,食品成分结构在基于骨架和指纹的多样性和结构复杂性方面较低,这可以通过 sp 碳原子的分数来衡量。这些结构特征与作为脂类的大量宏量营养素有关。通过对最大公共子结构的分析,对食品成分中的脂质进行了分解。使用不同的表示集,食品化学物质的化学多元宇宙表示法显示出比天然产物和 FDA 批准药物更大的化学空间覆盖范围。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1477/10900296/5f677dca2dca/ci3c01617_0011.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1477/10900296/8a7354000a9a/ci3c01617_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1477/10900296/498fae0fb07e/ci3c01617_0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1477/10900296/f304bd338a43/ci3c01617_0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1477/10900296/34dcc23c29c6/ci3c01617_0009.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1477/10900296/5f677dca2dca/ci3c01617_0011.jpg

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5
Systematic Analysis and Prediction of the Target Space of Bioactive Food Compounds: Filling the Chemobiological Gaps.生物活性食品化合物靶标空间的系统分析与预测:填补化学生物学空白。
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7
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